Technical Appendix: Workflow of `cond_indirect()`

Shu Fai Cheung & Sing-Hang Cheung

Goal

This technical appendix describes how cond_indirect() from the package manymome (Cheung & Cheung, 2024) works internally to extract the parameters and compute a conditional indirect effect.

cond_indirect()

Workflow of manymome::cond_indirect()

cond_indirect_effects()

Workflow of manymome::cond_indirect_effects()

indirect_i()

Main workflow

Workflow of manymome::indirect_i()

For Call get_prod(), see the workflow of Creating prods.

prods not supplied

Creating prods

Workflow of manymome::indirect_i(): Creating prods

Notes

Latent variables

If all variables along a path are latent variables, product term(s) must be identified by their names because raw scores are not available.

Default uses "_x_". For example, f1_x_f2 is the product term between f1 and f2.

Extracting Point Estimates and Variance-Covariance Matrix

When the point estimates or variance-covariance matrix of the point estimates are needed, they will be extracted internally using functions developed for the fit object, which can be a lavaan-class object, a list of the outputs from stats::lm(), or a lavaan.mi-class object generated by fitting a model to several datasets using multiple imputation.

Reference

Cheung, S. F., & Cheung, S.-H. (2024). manymome: An R package for computing the indirect effects, conditional effects, and conditional indirect effects, standardized or unstandardized, and their bootstrap confidence intervals, in many (though not all) models. Behavior Research Methods, 56(5), 4862–4882. https://doi.org/10.3758/s13428-023-02224-z